• Korean Journal of Optics and Photonics
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• v.14 no.6
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• pp.613-622
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• 2003

The multi-configurative microscopic system for inspecting the wire-bonding of reed frame is designed. Rays refracted by objective lens group which is composed of common lens group of x2 and x6 are splitted by beam-splitter, and Rays through the central region and the boundary region of the object imaged at x2 and x6 through imaging lens groups, respectively. The depth of wire structure on the reed frame has about $\pm$3 mm, in order to observe by uniform magnification without the dependency on the variation of objective distance generated by the depth of wire structure on the reed frame, imaging lens groups should be moved on nonlinear locus like mechanically compensated zoom lenses. The nonlinear equations for zoom locus are derived by using the Gaussian bracket. Refraction powers and positions of each groups are numerically determined by solving the equations, and initial design data for each groups is obtained by using Seidel third order aberration theory. The optimization technique is finally utilized to obtain this microscopic system.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.780-785
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• 2010

This paper introduces GP(Genetic Programming) based color detection model for an object detection and tracking. Existing color detection methods have used linear/nonlinear transformatin of RGB color-model and improved color model for illumination variation by optimization or learning techniques. However, most of cases have difficulties to classify various of colors because of interference of among color channels and are not robust for illumination variation. To solve these problems, we propose illumination robust and non-parametric multi-colors detection model using evolution of GP. The proposed method is compared to the existing color-models for various colors and images with different lighting conditions.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.11a
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• pp.101-103
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• 2011

Various desired performances of concrete cannot be always obtained by current conventional mix proportion methods for recycled aggregate concrete (RAC). This paper suggests a new design method of mix proportion for RAC to reduce the number of trial mixes using genetic algorithm (GA) which has been an optimization technique to solve the multi-object problem. In mix design method by GA, several fitness functions for the required properties of concrete, i.e., slump, strength, price, and carbonation speed coefficient were considered based on conventional data or fitness function. As a result, various optimum mix proportions for RAC that meet required performances were obtained and the risk evaluation was also conducted for selected mixtures.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.05b
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• pp.237-243
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• 1997

The ultimate object of our study is to minimize the release of radioactive material into the environment and to maximize the treatable amount of the generated wastes. In planning the practical operation of the system, however, the operating cost, Process economics and technical flexibility must also be considered. For dealing with these multiple criteria decision making Problems, we used a foal programming which is a kind of multi-objective linear programming. This method requires the decision maker to set goals for each objective that one wishes to attain.

• Smart Structures and Systems
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• v.23 no.2
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• pp.123-139
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• 2019

Impact forces induced by external object collisions can cause serious damages to civil engineering structures. While accurate and prompt identification of such impact forces is a critical task in structural health monitoring, it is not readily feasible for civil structures because the force measurement is extremely challenging and the force location is unpredictable for full-scale field structures. This study proposes a novel approach for identification of impact force including its location and time history using a small number of multi-metric observations. The method combines an augmented Kalman filter (AKF) and Genetic algorithm for accurate identification of impact force. The location of impact force is statistically determined in the way to minimize the AKF response estimate error at measured locations and then time history of the impact force is accurately constructed by optimizing the error co-variances of AKF using Genetic algorithm. The efficacy of proposed approach is numerically demonstrated using a truss and a plate model considering the presence of modelling error and measurement noises.

• Korean Journal of Optics and Photonics
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• v.29 no.1
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• pp.19-27
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• 2018

A change in object distance would generally change the magnification of an optical system. In this paper, we have proposed and designed a double-Gauss optical system with a fixed magnification and image surface regardless of any change in object distance, according to moving the lens groups a little bit to the front and rear of the stop, independently parallel to the direction of the optical axis. By maintaining a constant size of image formation in spite of various object-distance changes in a projection system such as a head-up display (HUD) or head-mounted display (HMD), we can prevent the field of view from changing while focusing in an HUD or HMD. Also, to check precisely the state of the wiring that connects semiconductor chips and IC circuit boards, we can keep the magnification of the optical system constant, even when the object distance changes due to vertical movement along the optical axis of a testing device. Additionally, if we use this double-Gauss optical system as a vision system in the testing process of lots of electronic boards in a manufacturing system, since we can systematically eliminate additional image processing for visual enhancement of image quality, we can dramatically reduce the testing time for a fast test process. Also, the Gaussian bracket method was used to find the moving distance of each group, to achieve the desired specifications and fix magnification and image surface simultaneously. After the initial design, the optimization of the optical system was performed using the Synopsys optical design software.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.224-238
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• 2004

Multi-modality image registration is a widely used image processing technique to obtain composite information from two different kinds of image sources. This study proposes an image registration method based on moment information and surface distance, which improves the previous surface-based registration method. The proposed method ensures stable registration results with low registration error without being subject to the initial position and direction of the object. In the preprocessing step, the surface points of the object are extracted, and then moment information is computed based on the surface points. Moment information is matched prior to fine registration based on the surface distance, in order to ensure stable registration results even when the initial positions and directions of the objects are very different. Moreover, surface comer sampling algorithm has been used in extracting representative surface points of the image to overcome the limits of the existed random sampling or systematic sampling methods. The proposed method has been applied to brain MRI(Magnetic Resonance Imaging) and PET(Positron Emission Tomography), and its accuracy and stability were verified through registration error ratio and visual inspection of the 2D/3D registration result images.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.163-173
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• 1997

Although numerous studies demonstrate that one technique outperforms the others for a given data set, it is hard to tell a priori which of these techniques will be the most effective to solve a specific problem. It has been suggested that the better approach to classification problem might be to integrate several different forecasting techniques by combining their results. The issues of interest are how to integrate different modeling techniques to increase the predictive performance. This paper proposes the post-model integration method, which tries to find the best combination of the results provided by individual techniques. To get the optimal or near optimal combination of different prediction techniques, Genetic Algorithms (GAs) are applied, which are particularly suitable for multi-parameter optimization problems with an object function subject to numerous hard and soft constraints. This study applies three individual classification techniques (Discriminant analysis, Logit model and Neural Networks) as base models for the corporate failure prediction. The results of composite predictions are compared with the individual models. Preliminary results suggests that the use of integrated methods improve the performance of business classification.

• Journal of the Korean Graphic Arts Communication Society
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• v.29 no.3
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• pp.77-96
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• 2011

Most of all manufacturing industries are pursuing the manufacturing process innovation through the production process automation but the printing industry still does not get out of the analog ways of the entire process compared the entire manufacturing industry. Today, many printing enterprises have the difficulties by the short for delivery, multi-item small amount printing, high quality, rise in raw material cost, drop in receiving order cost, and etc. The printing industry can get over these difficulties and issues by implementing the compact workflow line, merge with the others, automatization and networking, minimization of the repetitive operation, efficiency of the working process, optimization of the operators' value creation, minimization of cost and materials and fast make-ready. The object of this thesis establishes the experimental data and study cases applicable in the printing industry by having high labor productivity and work in line with printing industry processes through "lean printing system".

• Korean Journal of Materials Research
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• v.30 no.11
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• pp.627-635
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• 2020

3D printing technology is a processing technology in which 3D structures are formed by fabricating multiple 2D layers of materials based on 3D designed digital data and stacking them layer by layer. Although layers are stacked using inkjet printing to release various materials, it is still rare for research to successfully form a product as an additive manufacture of multi-materials. In this study, dispersion conditions are optimized by adding a dispersant to an acrylic monomer suitable for inkjet printing using Co₃O₄ and Al₂O₃. 3D structures having continuous composition composed of a different ceramic material are manufactured by printing using two UV curable ceramic inks whose optimization is advanced. After the heat treatment, the produced structure is checked for the formation and color of the desired crystals by comparing the crystalline analysis according to the characteristics of each part of the structure with ceramic pigments made by solid phase synthesis method.